Organic–inorganic interface simulation for new material discoveries

Abstract

Organic–inorganic interactions are of high importance in several biological processes and in modern nanobiotechnological applications. Despite its significance in interface sciences, the basic mechanism of biomolecules’ specific binding to a surface is still not well understood. Current experimental methods have not reached the level either to follow the dynamics of interactions at the picosecond scale or to observe the surface morphology at the nanoscale level. The increasing interest in bio‐interfaces particularly for engineering applications demands proteins or peptides to be designed to recognize the inorganic surface with high specificity. Molecular simulation has been well adopted in the past couple of decades to decipher the protein–surface interactions at different levels of time and length scales. Several molecular simulation methods such as quantum mechanics, atomistic, and coarse grain simulations were employed in this domain of research, but the continuous improvements in interfacial force field (FF) development, availability of experimental data and new sampling methods make the atomistic simulation more attractive due to the offered accurate representation of protein adsorption behavior at the atomic level. However, the exactitude of such simulations entirely depends on the applied FF parameters, conformational sampling, and the solvation effects. In this overview, we briefly summarize the applicability of different simulation methods and of interface FFs. We also present the recent advances in the simulation of protein–surface interactions, and the challenges posed by the current simulation methods to reproduce the exact phenomenon. Future directions in this research field are also discussed. WIREs Comput Mol Sci 2017, 7:e1277. doi: 10.1002/wcms.1277This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Computational Materials Science Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods